Abstract
This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex stations. A mathematical formulation of this problem is provided as a Mixed Integer Linear Program (MILP). However, the creation of an optimal new timetable is an NP-hard problem; therefore, the MILP can be solved for easy cases, computation time being impractical for more complex examples. In these cases, a heuristic approach is provided that makes use of genetic algorithms to find a good solution jointly with heuristic techniques to generate an initial population. The algorithm was applied to a number of problem instances producing feasible, though not optimal, solutions in several seconds on a laptop, and compared to other proposals. Some improvements are suggested to obtain better results and further improve computation time. Rail transport is recognized as a sustainable and energy-efficient means of transport. Moreover, each freight train can take a large number of trucks off the roads, making them safer. Studies in this field can help to make railways more attractive to travelers by reducing operative cost, and increasing the number of services and their punctuality. To improve the transit system and service, it is necessary to build optimal train scheduling. There is an interest from the industry in automating the scheduling process. Fast computerized train scheduling, moreover, can be used to explore the effects of alternative draft timetables, operating policies, station layouts, and random delays or failures.
Highlights
Sustainability in the context of railway operation is a multidimensional aspect
This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex stations
Each freight train can take a large number of trucks off the roads, making them safer
Summary
Sustainability in the context of railway operation is a multidimensional aspect. Train operators are interested in efficiency in terms of the availability and access costs of railway infrastructure, while users of railway services place emphasis on transport punctuality/reliability or speed [1]. In the context mentioned before, delay-aware scheduling becomes vital for efficient resource assignment in complex railway scenarios, improving the level of safety and punctuality These terms relate railway sustainability that is increasingly socially demanded to the reliability and availability of the solution. Research for this study was conducted in four main steps: (i) literature review focused on train scheduling on railway networks composed of busy complex stations; (ii) design of a mathematical model including the complexity of the scenario; (iii) providing heuristics based on genetic algorithms to solve the problem; and (iv) evaluation of both proposals applied on the request of a real railway operator, compared with other solutions.
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